Classifying Biometric Systems Users among the Doddington Zoo: Application to Keystroke Dynamics
Denis Migdal, Ilaria Magotti, Christophe Rosenberger
2021
Abstract
Doddington zoo defines four categories of users when using a biometric system related to their difficulty to be recognized or attacked. In this paper, we propose an original work consisting in predicting for any biometric modality the associated animal in the Doddington menagerie related to a user given few captured biometric samples. Such a prediction could be useful for many applications, as for example, to adapt the behavior of biometric systems to each user. In this work, we apply this methodology to keystroke dynamics as it is an interesting behavioral biometric modality for user authentication. It consists in analyzing the way of typing of a user in order to recognize him/her. We use a significant keystroke dynamics dataset and we demonstrate through experimental results the benefit of the proposed approach.
DownloadPaper Citation
in Harvard Style
Migdal D., Magotti I. and Rosenberger C. (2021). Classifying Biometric Systems Users among the Doddington Zoo: Application to Keystroke Dynamics. In Proceedings of the 18th International Conference on Security and Cryptography - Volume 1: SECRYPT, ISBN 978-989-758-524-1, pages 747-753. DOI: 10.5220/0010577507470753
in Bibtex Style
@conference{secrypt21,
author={Denis Migdal and Ilaria Magotti and Christophe Rosenberger},
title={Classifying Biometric Systems Users among the Doddington Zoo: Application to Keystroke Dynamics},
booktitle={Proceedings of the 18th International Conference on Security and Cryptography - Volume 1: SECRYPT,},
year={2021},
pages={747-753},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010577507470753},
isbn={978-989-758-524-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 18th International Conference on Security and Cryptography - Volume 1: SECRYPT,
TI - Classifying Biometric Systems Users among the Doddington Zoo: Application to Keystroke Dynamics
SN - 978-989-758-524-1
AU - Migdal D.
AU - Magotti I.
AU - Rosenberger C.
PY - 2021
SP - 747
EP - 753
DO - 10.5220/0010577507470753